After having selected the best model with cross-validation, for how long should I train it?
Short answer: training "duration" or number of epochs/updates should be cross-validated too: you want to early-stop your training to prevent overfitting.

Longer answer:


  Think of accuracy on the validation set as an estimate of accuracy on future data, given the value of some hyperparameter. In this case, the hyperparameter of interest is the number of training epochs. So: for each CV fold, train the network (e.g. up to some maximum number of epochs). After each epoch, record accuracy on the validation set. Compute the average validation set accuracy (across CV folds) for each number of epochs. Choose the number of epochs that maximizes this value.


https://stats.stackexchange.com/questions/298084/k-fold-cross-validation-for-choosing-number-of-epochs